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E&ICT Academy, IIT Roorkee Programs

AI-Powered Embedded & IoT Program

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Build Real Embedded Systems. Get Placed. 6-Month Job-Ready Program with Mentorship by IIT Alumni & Industry Experts

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Wind Speed 12km/h

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Admission Closes

20 May, 2026

Program Duration

6 Months

Learning Format

Offline, Online

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Key Highlights of this
AI-Powered Embedded & IoT Program

Career-Ready Curriculum: Skills aligned with industry demands

Certification: Official certificate from The IoT Academy.

Real-Time Projects: Build smart sensors, autonomous devices & IoT systems

AI on Microcontrollers: Deploy ML Models with Ease

Live Mentorship:  Weekly Q&A with embedded AI experts

Hands-On Hardware: Work with dev boards, sensors, modules, and AI accelerators through practical IoT Training in Noida.

Expert Faculty: In this Internet of Things Course, learn from IIT Alumni & Embedded AI Industry Experts.

Placement Assistance:Dedicated career support, resume building & interview preparation

Admission Closes On 20 May 2026

Industry-Relevant Concepts: TinyML, Edge AI & Neural Networks on microcontrollers
1:1 Doubt & Mentor Support: Anytime guidance from embedded AI specialists
Learn from the Best: Faculty with hands-on industry & research experience
Real Projects, Real Portfolio: Hardware-based projects for job-ready credibility

Our Trusted Academic Partners

E&ICT Academy IIT Roorkee

E&ICT Academy IIT Guwahati

E&ICT Academy IIT Kanpur

IIT Jodhpur

NIT Patna

RFRF Foundation

ASTU Guwahati

IIT Bhilai

ABES College

MSIT College

Himachal Pradesh University

IPEC College

Integrated with
TinyML & Edge AI Technologies

  • AI-Powered Embedded Systems Learn how AI integrates with embedded systems to build intelligent hardware solutions. Work with microcontrollers, sensors, and AI frameworks to create smart devices capable of real-time processing and automation.
  • Edge AI & TinyML Explore how to deploy lightweight AI models directly on embedded and IoT devices. Master TinyML techniques to enable fast, low-power, and offline AI decision-making on edge hardware.
  • Smart AIoT Applications Build next-generation AIoT solutions by combining Artificial Intelligence with IoT technologies. Develop connected systems that collect data, analyze patterns, and automate actions for smart homes, industries, healthcare, and robotics.

What Makes This
AI-Powered Embedded & IoT Program Different

Learn how AI works in real devices and systems. This program teaches you to build smart, AI-powered gadgets step by step. In 16 weeks, you will do live projects, grow your skills, and get full support to find a job.

Career Transformation: Build strong embedded systems skills and learn AI to work with smart devices.

Hands-On Learning:  Work on 5 live Lab projects in 16 weeks and get real IoT Training in Noida.

Core Skills: Learn to run neural networks on microcontrollers and build edge AI apps.

Professional Support:  Build your portfolio and get placement help to start your career.

Admission Closes On 20th May

See what you’ll learn

  • 100+ hours of live, hands-on embedded AI training
  • 9+ industry-grade projects across domains
  • Master TinyML, Edge AI, RTOS & IoT system design
We respect your privacy. Your data will be used only to contact you about The IoT Academy programs.

Trusted by Leading Corporate Partners

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Tools & Technologies You Will Learn

STM32CubeIDE
Keil MDK
TensorFlow Lite
Edge Impulse
OpenMV
FreeRTOS
Zephyr OS
Node-RED
Python for Embedded
C/C++ Programming
ARM Mbed
Raspberry Pi
MATLAB Simulink
ESP32
NVIDIA Jetson

Career Opportunities

An AI Embedded Systems Architect builds the intelligence behind next-generation devices—turning data into real-time decisions. From edge AI to connected systems, they architect seamless hardware-software ecosystems, enabling smarter, faster, and more adaptive technologies.

Hiring Companies

An IoT & Embedded AI Developer brings intelligence to the edge—turning everyday devices into smart, responsive systems. From firmware to AI deployment, they create solutions that sense, learn, and adapt in real time

Hiring Companies

An AIoT Specialist builds intelligent ecosystems where devices don’t just connect—they think. By combining IoT and AI, they create systems that sense, analyze, and act in real time, powering the next generation of smart technology.

Hiring Companies

Skills You Will Master

Embedded Programming

C/C++ for microcontrollers & real-time systems

AI on Microcontrollers:

Deploy TinyML & deep learning on edge hardware

Hardware Interfacing:

Control sensors, actuators & IoT modules

RTOS & Linux:

FreeRTOS & Embedded Linux for real-time apps

Edge Intelligence:

On-device AI with low-latency processing

Sensor Fusion:

Capture, analyze & act on multi-sensor data

Wireless Protocols:

WiFi, Bluetooth & LoRa for IoT connectivity

End-to-End IoT Design:

Build complete cloud-connected AI-IoT systems

Why You Should Choose Embedded Systems with AI Course Now?

The Embedded AI market is booming, and companies are hiring fast. Gain the exact skills & hands-on experience to land high-paying roles in this high-growth field.
Master Embedded C, AI deployment & RTOS hands-on
Build autonomous devices for next-gen IoT
10+ real-world projects with expert guidance
Enter a field with 40%+ annual demand growth

Strength of Embedded Systems with AI Certification Course

Gain a strong foundation in Embedded Systems powered by AI through in-depth modules designed with the latest industry research and best practices.

In-depth modules built on the latest embedded AI research and industry practices.
Live case studies from automotive, healthcare, and industrial automation sectors.
Peer collaboration in small cohorts for focused learning and project development.
Continuous support from mentors and technical teaching assistants.
Lifetime access to course updates, new AI frameworks, and hardware integrations.
Capstone project reviewed and certified by embedded AI industry experts.
Final Enrollment Phase

Last Batch Almost Full

Limited Seats Remaining

03 Days
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09 Hours
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31 Minutes
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26 Seconds

Profiles in IoT & Embedded Systems

Embedded AI Engineer
Edge Computing Specialist
IoT Systems Developer
Automotive Electronics Engineer
Smart Device Developer
Embedded Machine Learning Engineer
Industrial Automation Engineer
Robotics Engineer
Firmware Engineer
IoT Developer
Drone & UAV Systems Engineer
Computer Vision Engineer

Master AI-Powered Embedded & IoT Course Curriculum

  • Evolution of embedded systems
  • Microcontrollers vs Microprocessors
  • Embedded applications in automotive, healthcare, consumer electronics, and IoT
  • Development tools: IDEs, toolchains, debuggers

Lab: Setting up Arduino/ESP32 or STM32 development board, "Hello World" LED blink.

  • C basics for embedded (data types, pointers, bit manipulation)
  • Memory organization (stack, heap, registers)
  • I/O mapping and register-level programming

Lab: GPIO programming, reading switches, driving LEDs.

  • ADC/DAC concepts
  • Timers, PWM, interrupts
  • Serial protocols: UART, I2C, SPI

Lab: Interface a temperature sensor + display output on serial monitor.

  • Sensor & actuator overview
  • Memory (EEPROM, Flash, SRAM)
  • Power supply, clock system, watchdog timers
  • Intro to Embedded Linux

Lab: Work with external EEPROM, log sensor data.

  • Multitasking concepts
  • Scheduling (preemptive, cooperative)
  • Tasks, semaphores, queues, mutexes
  • FreeRTOS / Zephyr basics

Lab: Create multiple tasks with priorities on FreeRTOS.

  • Bootloaders & kernel basics
  • Device drivers introduction
  • Cross-compilation, GPIO access from Linux

Lab: GPIO programming on Raspberry Pi.

  • WiFi, Bluetooth/BLE 5, Zigbee
  • LPWAN: LoRaWAN, NB-IoT
  • Application protocols: MQTT, CoAP, HTTP

Lab: Send sensor data to MQTT broker using ESP32/STM32 + WiFi.

  • Security threats in IoT
  • Encryption (TLS/DTLS)
  • Secure boot & firmware signing
  • OTA firmware updates

Lab: Implement a secure MQTT connection with TLS.

  • Edge, Gateway, Cloud
  • Device identity & provisioning
  • Scalability in IoT systems

Lab: Set up an IoT gateway to forward sensor data to cloud.

  • AWS IoT Core, Azure IoT Hub, Google IoT
  • Open-source platforms (ThingsBoard, Node-RED, Mosquitto)
  • REST APIs, WebSockets

Lab: Push IoT sensor data to ThingsBoard dashboard.

  • Data storage (SQL/NoSQL, Time-series DBs)
  • Visualization tools (Grafana, Power BI)
  • IoT analytics use-cases

Lab: Build a real-time dashboard for temperature & humidity monitoring.

  • Introduction to TinyML (TensorFlow Lite Micro, Edge Impulse)
  • Running ML on constrained devices
  • Use cases: anomaly detection, predictive maintenance

Lab: Deploy a simple ML model on MCU for gesture recognition.

  • Power management techniques
  • Battery optimization & estimation
  • Energy harvesting (solar, vibration, RF)

Lab: Implement sleep/wake cycles to extend battery life.

  • Industry 4.0 concepts (IIoT)
  • PLC/SCADA integration
  • Protocols: OPC-UA, Modbus
  • Smart home & Matter protocol (latest standard)

Lab: Build a simple smart home setup (e.g., light automation with mobile app).

  • Proposal & system design
  • Hardware selection & firmware development
  • Cloud integration & security layer
  • Testing & debugging
  • Performance analysis (latency, power, security)
  • Final presentation & submission
  • What is AIoT?
  • Use cases: predictive maintenance, smart cities, healthcare
  • AI workflow (data → model → deployment)

Lab: Collect sensor data for AI training.

  • ML concepts: classification, regression, clustering
  • Supervised vs unsupervised learning
  • Libraries: Scikit-learn, TensorFlow

Lab: Train a simple ML model on collected IoT data.

  • Introduction to TinyML & TensorFlow Lite Micro
  • Limitations of constrained devices
  • ML optimization (quantization, pruning)

Lab: Deploy gesture recognition model on Arduino/ESP32.

  • Edge AI with cameras
  • Object detection basics (MobileNet, YOLO-lite)
  • Use cases: surveillance, smart farming

Lab: Run face/object detection on Raspberry Pi.

  • Integration of AI models into IoT pipelines
  • Edge inference vs cloud inference
  • Hybrid AIoT design patterns

Lab: Deploy anomaly detection model at IoT edge.

  • Vibration analysis in IIoT
  • Time-series AI models (RNN, LSTM)
  • Case study: Motor fault detection

Lab: Train LSTM model on vibration dataset.

  • RL basics (agents, states, rewards)
  • Applications: smart energy management, traffic control

Lab: RL-based thermostat control simulation.

  • Generative models for IoT (predictive simulations, synthetic data)
  • LLMs for IoT management & automation
  • Chatbots integrated with IoT devices

Lab: Build chatbot that queries IoT device data.

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Embedded Systems with AI Course Certification

Upon successful completion, you will receive The IoT Academy Embedded Systems with AI Integration Certificate, a mark of your ability to design and implement intelligent embedded systems solutions.

Globally Recognized Certification

Career Support

Credibility and Validation

Course Certificate

Internship Certificate

Embedded Systems with AI Course Fee Structure

Special Corporate Enrollment Pricing Enroll before 20 May 2026 to avail additional 10% early bird discount.

₹45,999/-

No-cost EMI available | Scholarships up to 30% for eligible students

Avail Scholarship Up To 30%

Start Your Learning Journey, Today
Batch Almost Full - Only 7 Seats Left
  • Align your goals with a Learning Consultant.
  • Shape your learning path with an industry expert.
  • Get evaluated and access scholarships.
  • Align your goals with a Learning Consultant.

Admission Process

The program follows 4 simple steps. Selected candidates receive an admission offer, confirmed after fee payment.
  • 01

    Submit Your Application Fill out the online form & our Admissions team will reach out within 24 hours.

  • 02

    Profile Screening Our team reviews your background & assesses program fitment for the best results.

  • 03

    Scholarship & Offer Letter Eligible candidates receive a merit-based scholarship offer & official admission letter.

  • 04

    Confirm Seat & Begin Learning Complete your fee payment, get login credentials & join your assigned batch immediately

Admission Form

Upload Your Resume

Drag & Upload Or Choose File To Upload (only pdf, doc and docx having max size 2MB)

Live Industry-Based Projects

Industry projects are a part of our online Embedded Systems with AI Certification course. Such projects will ensure exposure to real-world experience for starting a career in Embedded Systems.

Course Focus: Practical Embedded AI learning via live industry projects.

Hands-On Tasks: Create intelligent devices with AI on resource-constrained microcontrollers.

Skill Development: Master AI-embedded systems with real-world, hands-on practice

Career Advantages: Build a job-ready portfolio that stands out to top recruiters.

AI-powered face recognition door lock

Build an AI-powered face recognition door lock that unlocks only when an authorized face is detected

Tools Learned
predictive maintenance system

Develop a predictive maintenance system that analyzes vibration data to detect failures in industrial motors

Tools Learned
AI-based smart automation system

Create an AI-based smart automation system integrating sensors and machine learning for real-world applications

Tools Learned
Health Monitoring Wearable
Health Monitoring Wearable

Build an AI-powered wearable device that monitors vital signs and detects health anomalies in real time

Tools Learned
Smart Traffic Control System
Smart Traffic Control System

Develop an AI-based traffic control system that adjusts signals dynamically based on real-time traffic density

Tools Learned
AI Intrusion Detection System
AI Intrusion Detection System

Create an AI-based intrusion detection system that identifies human movement and reduces false alarms

Tools Learned
Download the brochure to explore all 9+ projects, tools & program details in one place.

Our Past Success Stories

Our learners’ voices speak louder than promises. These trusted testimonials highlight how The IoT Academy has empowered individuals to gain new skills, unlock opportunities, and achieve their dreams.
vitoka
Vitoka H Sema
My name is Vitoka H Sema from Nalan University. I came to The IoT Academy for a 4-week winter training on IT and Embedded Systems. I did many projects and the teaching was very practical. It was my first experience of this kind of training, and I learned a lot. I am very thankful to all the faculty at IoT Academy.
Sohail Hamza
My name is Sohail Hamza from Kashmir. I searched on Google for the best IoT institute for hardware training and found The IoT Academy. Here, I worked on major IoT projects. The teaching is more practical than theoretical, which most other institutes do not offer. I got real hands-on experience here. Thank you, The IoT Academy.
Atif Ahemad
I am Atif Ahmed from Srinagar, J&K. I came to The IoT Academy for winter training in electronics hardware. We checked many institutes, but this was the best. The faculty is very helpful and calm. We did projects like Traffic Monitoring, Ultrasonic Distance Sensing, and worked with Node MCU. I recommend everyone to come here.
Adnan
I am Adnan from IUST. I joined the 4-week Embedded Systems and IoT course at IoT Academy. We started with basics, then learned C Programming, and did Arduino projects like a Traffic Light System, Ultrasonics, and LDR. After that, we moved to IoT and did projects like Weather Monitoring. I recommend The IoT Academy to everyone.
Qunain Bashir
I am from Kashmir and came to The IoT Academy for winter training. It was a brilliant experience for my friends and me. We worked on many new projects under our mentor Devana, who helped us a lot. The faculty is very cooperative. We learned about ESP boards and many other new technologies. Thank you, IoT Academy.
Vaibhav Raj Singh
My name is Vaibhav Raj Singh from MIT Scholar. I did a 2-month internship at The IoT Academy. I learned about STM32, SDR, Bison Board, and communication protocols. I worked on real projects and gained good practical experience. It was a great experience that improved my technical skills.
Anand Kumar
I am Anand Kumar from Nalan University. I joined the 4-week Embedded Systems and IoT course at The IoT Academy. The learning was very practical. We did projects like Smart Street Light and Object Avoidance using Ultrasonic and LDR sensors. The teaching style makes it easy to learn. I suggest everyone join this course. Thank you.
Ankur Verma
I am Ankur from MDA. I did a 2-month IoT internship at The IoT Academy. I worked on real-world topics and advanced communication protocols. The experience was very good and helped me understand real industry scenarios. Everyone at IoT Academy supported and guided me throughout. Thank you.
Tanishka Singh
I am Tanishka Singh from MITS Gwalior. During an industrial visit, I got an internship at Unique Converse Technology, parent company of The IoT Academy. I worked on Smart Street Light, Industrial 4.0, Smart Agriculture, and gained hands-on PCB and PLC experience. Highly recommended.

Early Bird Offer Ends 20 May 2026 - Don't Miss Out!

Start Your AI-Powered Embedded & IoT Journey Today!

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Frequently Asked Questions (FAQs)

It teaches you how to build smart devices using electronics and AI, like robots, drones, and smart gadgets used in real industries.

Embedded systems are the tiny computers inside devices like phones and cars. When AI is added, these devices can think and make decisions on their own without the internet. This is called Edge AI.

Electronics basics, circuits, sensors, Embedded C/C++, Arduino, Raspberry Pi, ESP32, Wi-Fi, Bluetooth, I²C, SPI, RTOS, TinyML, Edge AI, IoT and cloud connectivity.

3 months or 6 months, both with live online classes and recorded backups. Delhi/NCR students may get lab access too.

ECE, EEE, Mechatronics, CSE graduates, diploma holders in electronics, working professionals in hardware, and tech hobbyists.

No. We start from the basics. A little electronics knowledge is helpful but not required.